On 19 Aug 2003 05:57:09 -0700, [EMAIL PROTECTED] (Louis T) wrote: > Rich Ulrich <[EMAIL PROTECTED]> wrote in message news:<[EMAIL PROTECTED]>... > > [ snip, previous] > > > Okay. I think you are asking about describing a small fraction, > > and putting a Confidence Limit around it. That part of the > > problem, the numeric part, is not too hard. > > That's it > > > For a small proportion, we can consider the "counts" to be > > numbers that are distributed as Poisson: And in that case, > > the square root of the count is very close to being "normal" > > with standard error of 1/2. > > From my small knowledge, it looks like an application of the Central > Limit theorem. The distribution of the sample's means is closing to a > "normal" distribution, whatever the distribution of the population is. >
CLT? No. The CLT has to do with the behavior of a sum. I am describing the behavior of a transformation. [SE means "standard error" which is SD/sqrt(N) where SD is standard deviation. Snip, to end.] -- Rich Ulrich, [EMAIL PROTECTED] http://www.pitt.edu/~wpilib/index.html "Taxes are the price we pay for civilization." Justice Holmes. . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
